<p>Heating, ventilation, and air conditioning (HVAC) systems are essential for maintaining indoor comfort, air quality, and operational continuity in educational buildings, particularly in hot and humid regions like Saudi Arabia. Chillers are the most energy-intensive and failure-prone components. This paper proposes a fuzzy failure mode and effects analysis (Fuzzy-FMEA) model aimed at assessing the risk of chiller station failures in academic buildings by enhancing failure mode prioritization through addressing subjectivity and uncertainty. The proposed model is developed, trained, and validated using real failure incidents and expert input. A total of 31 real-world chiller station failure incidents are identified based on historical maintenance records and interviews with experts across multiple academic facilities. Each failure mode was evaluated using the proposed risk assessment approach. The findings reveal that chiller surging, with a Fuzzy Risk Priority Numbers (F-RPN) of 62.5, abnormal sound in the chiller, with an F-RPN of 60.8, and overheating of oil temperature, with an F-RPN of 59.8, are among the most critical failures. Conversely, the unavailability of water in the tank of a cooling tower, with an F-RPN of 13.30, presents the lowest risk. The validation results confirmed the reliability of the fuzzy model system, achieving a normalized mean squared error (NMSE) of 4.12% and a root mean square error (RMSE) of 4.88%, within the acceptable error margin. The proposed methodology serves as an effective decision-making tool for prioritizing failures based on risk, thereby enhancing system reliability and facilitating data-driven facility management amidst uncertainty.</p>